Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Objective To construct a support system that facilitates the participation of children with special needs(CSN)in physi-cal activity within the context of inclusive education.Methods Based on World Health Organization(WHO)health promoting school(HPS)framework,and integrating WHO International Classification of Functioning,Disability and Health(ICF)as well as the WHO guidelines on physi-cal activity,a systematic and multidimensional support framework was developed.Results In the context of inclusive education,the primary forms of physical activity for CSN included physical educa-tion classes and extracurricular sports activities.A comprehensive support system was developed at macro-,me-so-and micro-levels.At the macro-level,the framework called for the establishment of inclusive physical educa-tion and activity-related policies,accessible and universally designed physical environments,inclusive activity climates,and integrated community resources.At the meso-level,it emphasized creating a supportive profession-al development environment for inclusive physical education teachers,equipping them with skills in inclusive pedagogy,classroom management and extracurricular activity planning.At the micro-level,it focused on the de-sign of physical education curricula tailored to the physical activity and motor development needs of CSN,the es-tablishment of individualized learning support mechanisms,and encouraging active participation in physical edu-cation and physical activities.Conclusion To address the physical activity and educational needs of CSN in inclusive education settings,a three-tiered support system has been constructed.The macro-level involves policy,environment and community;the meso-level focuses on teachers and instructional practices;and the micro-level targets students'learning,motor devel-opment and health.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Osteoarthritis (OA) is one of the most prevalent joint disorders, with aging considered a primary, irreversible factor contributing to its progression. Telomere-related cellular senescence may be a crucial factor influencing the OA process, yet biomarkers for OA based on telomere-related genes have not been clearly identified. The datasets GSE51588, GSE12021, and GSE55457 were retrieved from the Gene Expression Omnibus database. Initially, R software was utilized to identify differentially expressed genes between OA and normal samples. Subsequently, differentially expressed telomere-related genes (DETMRGs) were obtained, and their functional enrichment was analyzed. Feature genes for OA diagnosis were selected from DETMRGs using a combination of least absolute shrinkage and selection operator, support vector machine-recursive feature elimination, and Random Forest algorithms. The diagnostic value of these feature genes was then validated through receiver operating characteristic (ROC) curves and decision curve analysis. Additionally, CIBERSORT and xCell were employed to assess the infiltration of immune cells in OA tissues.Finally, potential drugs targeting candidate genes were predicted. Three telomererelated genes, PGD, SLC7A5, and TKT, have been identified as biomarkers for OA diagnosis and were confirmed through ROC diagnostic tests. The immune infiltration of mast cells, neutrophils, common lymphoid precursors, and eosinophils associated with PGD, SLC7A5, and TKT was reduced. Recognizing telomere-related genes PGD, SLC7A5, and TKT as potential diagnostic biomarkers for OA is significant, as it offers valuable insights into the role of telomere-related genes in OA. This discovery also provides valuable information for the diagnosis and treatment of OA.

Objective To develop a competency framework for teachers in inclusive education settings based on World Health Orga-nization rehabilitation competency framework(RCF).Methods Based on the five core competency domains of RCF,along with its core values and beliefs,this study analyzed the specific competency requirements for teachers in inclusive education settings,and summarized the specific competencies,behavioral requirements,and core values and beliefs within these five domains.Additionally,Inter-national Classification of Functioning,Disability and Health(ICF)was used to supply the competency frame-work from a functional perspective.Results RCF-based teacher competency framework for inclusive education settings encompassed five core domains and two foundational components.In the practice domain,the framework emphasized a student-and family-centered approach,requiring flexible teaching strategies to meet individualized needs.In the professionalism domain,it highlighted educational equity,ethical responsibility and rights of students with special needs.In the learning and development domain,it underscored continuous learning and professional growth for teachers to enhance adapt-ability and innovation in inclusive education.In the management and leadership domain,it stressed teamwork and resource integration to improve the quality of inclusive education services.In the research domain,it encour-aged teachers to integrate evidence-based practices into their teaching to ensure scientific and empirical educa-tional decision-making.Additionally,the core values emphasized respect,equity and inclusion,while the beliefs reflected confidence in each student's potential and a commitment to individualized support.Based on ICF,the specialized competencies for teachers in inclusive education primarily involved five aspects:integrating educa-tion and rehabilitation,functional assessment and individualized education planning,assistive technology,acces-sible learning environments,and digital empowerment technologies.Conclusion Based on RCF and ICF,a multidimensional and composite competency framework has been developed for teachers in inclusive education settings,which providing a systematic theoretical foundation for competency de-velopment,assessment and training,upholding a individual-centered approach,and emphasizing educational eq-uity and holistic student development.

Objective To construct a support system that facilitates the participation of children with special needs(CSN)in physi-cal activity within the context of inclusive education.Methods Based on World Health Organization(WHO)health promoting school(HPS)framework,and integrating WHO International Classification of Functioning,Disability and Health(ICF)as well as the WHO guidelines on physi-cal activity,a systematic and multidimensional support framework was developed.Results In the context of inclusive education,the primary forms of physical activity for CSN included physical educa-tion classes and extracurricular sports activities.A comprehensive support system was developed at macro-,me-so-and micro-levels.At the macro-level,the framework called for the establishment of inclusive physical educa-tion and activity-related policies,accessible and universally designed physical environments,inclusive activity climates,and integrated community resources.At the meso-level,it emphasized creating a supportive profession-al development environment for inclusive physical education teachers,equipping them with skills in inclusive pedagogy,classroom management and extracurricular activity planning.At the micro-level,it focused on the de-sign of physical education curricula tailored to the physical activity and motor development needs of CSN,the es-tablishment of individualized learning support mechanisms,and encouraging active participation in physical edu-cation and physical activities.Conclusion To address the physical activity and educational needs of CSN in inclusive education settings,a three-tiered support system has been constructed.The macro-level involves policy,environment and community;the meso-level focuses on teachers and instructional practices;and the micro-level targets students'learning,motor devel-opment and health.

Objective To develop a competency framework for teachers in inclusive education settings based on World Health Orga-nization rehabilitation competency framework(RCF).Methods Based on the five core competency domains of RCF,along with its core values and beliefs,this study analyzed the specific competency requirements for teachers in inclusive education settings,and summarized the specific competencies,behavioral requirements,and core values and beliefs within these five domains.Additionally,Inter-national Classification of Functioning,Disability and Health(ICF)was used to supply the competency frame-work from a functional perspective.Results RCF-based teacher competency framework for inclusive education settings encompassed five core domains and two foundational components.In the practice domain,the framework emphasized a student-and family-centered approach,requiring flexible teaching strategies to meet individualized needs.In the professionalism domain,it highlighted educational equity,ethical responsibility and rights of students with special needs.In the learning and development domain,it underscored continuous learning and professional growth for teachers to enhance adapt-ability and innovation in inclusive education.In the management and leadership domain,it stressed teamwork and resource integration to improve the quality of inclusive education services.In the research domain,it encour-aged teachers to integrate evidence-based practices into their teaching to ensure scientific and empirical educa-tional decision-making.Additionally,the core values emphasized respect,equity and inclusion,while the beliefs reflected confidence in each student's potential and a commitment to individualized support.Based on ICF,the specialized competencies for teachers in inclusive education primarily involved five aspects:integrating educa-tion and rehabilitation,functional assessment and individualized education planning,assistive technology,acces-sible learning environments,and digital empowerment technologies.Conclusion Based on RCF and ICF,a multidimensional and composite competency framework has been developed for teachers in inclusive education settings,which providing a systematic theoretical foundation for competency de-velopment,assessment and training,upholding a individual-centered approach,and emphasizing educational eq-uity and holistic student development.

Recombinant human interferon α2b(rhIFNα2b)is widely used as an antiviral therapy agent for the treatment of hepatitis B and hepatitis C.The current identification test for rhIFNα2b is complex.In this study,an anti-rhIFNα2b nanobody was discovered and used for the development of a rapid lateral flow strip for the identification of rhIFNα2b.RhIFNα2b was used to immunize an alpaca,which established a phage nanobody library.After five steps of enrichment,the nanobody I22,which specifically bound rhIFNα2b,was isolated and inserted into the prokaryotic expression vector pET28a.After subsequent purification,the physicochemical properties of the nanobody were determined.A semiquantitative detection and rapid identification assay of rhIFNα2b was developed using this novel nanobody.To develop a rapid test,the nanobody I22 was coupled with a colloidal gold to produce lateral-flow test strips.The developed rhIFNα2b detection assay had a limit of detection of 1 μg/mL.The isolation of I22 and successful construction of a lateral-flow immunochromatographic test strip demonstrated the feasibility of performing ligand-binding assays on a lateral-flow test strip using recombinant protein products.The principle of this novel assay is generally applicable for the rapid testing of other com-mercial products,with a great potential for routine use in detecting counterfeit recombinant protein products.